This description relates to presenting content items in combination with publications, and more particularly to predicting viewer interest levels associated with different combinations of publications and content items.
In at least some known systems, a server computing device transmits a publication (e.g., a video or a web page) in combination with a content item (e.g., an advertisement) to a client computing device for display on the client computing device. The selection of a content item to be transmitted in combination with the publication is based on matching a content item to a set of keywords (“vertical”) associated with the publication. In some known implementations, the content item is displayed as a video clip on the client computing device prior to showing the publication, which is also a video. A user of the client computing device may choose to skip the content item, for example after five seconds of the content item have played, to view the publication. Such an occurrence lowers a view-through-rate (“VTR”) assigned to the content item. In other implementations, a content item is displayed within a publication that is a web page. If the user clicks on the content item to visit a landing page, the click-through-rate (“CTR”) of the content item increases. The VTR and the CTR are both indications of viewer interest levels in their respective content items. It would be beneficial to have a system for predicting viewer interest levels for different combinations of publications and content items to serve more relevant content items for any given publication.